Featureless Similarity

Assessing the similarity between cases is a key aspect of the retrieval phase in Case-Based Reasoning (CBR). In most CBRwork, similarity is assessed based on feature-value descriptions of cases using similarity metrics which use these feature values. Infact it might be said that this notion of a feature-valuere presentation is a defining part of the CBR world-view -- it underpins the idea of a problem space with cases located relative to each other in this space. Recently a variety of similarity mechanisms have emerged that are not feature-based. Some of these ideas have emerged in CBR research but many of them have arisen in other areas of data analysis. In fact research on Support VectorMachines (SVM) is a rich source of novel similarity representations because of the emphasis on encoding domain knowledge in the kernel function of the SVM. In this paper we review these novel featureless similarity measures and assess the implications these measures have for CBR research.